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Graduate Exam Abstract


minda Le

Ph.D. Final

March 11, 2013, 2pm

N/A

MICROPHYSICAL RETRIEVAL AND PROFILE CLASSIFICATION FOR GPM DUAL-FREQUENCY PRECIPITATION RADAR AND THE GROUND VALIDATION


Abstract: The Global Precipitation Measurement (GPM) mission is planned to be the next satellite mission following Tropical Rainfall Measurement Mission (TRMM) jointly by National Aeronautic and Space Administration (NASA) of USA and the Japanese Aerospace Exploration Agency (JAXA) with additional partners namely the Centre National d’Études Spatiales (CNES), the Indian Space Research Organization (ISRO), the National Oceanic and Atmospheric Administration (NOAA), the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), and others. The core satellite of GPM mission will be equipped with a dual frequency precipitation radar (DPR) operating at Ku- (13.6 GHz) and Ka- (35.5 GHz) band with the capability to cover 65 latitude of the earth. One primary goal of the DPR is to improve accuracy in estimation of drop size distribution (DSD) parameters of precipitation particles. The estimation of the DSD parameters helps to achieve more accurate estimation of precipitation rate. The DSD is also centrally important in the determination of the electromagnetic scattering properties of precipitation media. The combination of data from the two frequency channels, in principle, can provide more accurate estimates of DSD parameters than the TRMM Precipitation radar (TRMM PR) with Ku- band channel only. In this research, a methodology is developed to retrieve DSD parameters for GPM-DPR. Profile classification is a critical module in the microphysical retrieval system for GPM-DPR. The nature of microphysical models and equations to use in the DSD retrieval algorithm are determined by the precipitation type of each profile and the phase state of hydrometeors. In the GPM era, Ka- band channel enables the detection of light rain or snowfall in the mid- and high- latitudes compared to the TRMM PR (Ku- band only). GPM-DPR offers dual-frequency observations (measured reflectivity at Ku- band:Z_m (K_u ) and measured reflectivity at Ka- band: Z_m (K_a )) along each vertical profile, which provide additional information for investigating the microphysical properties using the difference in measured radar reflectivities at the two frequencies, a quantity often called the measured dual-frequency ratio (DFRm) can be defined (DFRm=Z_m (K_u )-Z_m (K_a ) ). Both non-Rayleigh scattering effects and attenuation difference control the shape of the DFRm profile. Its pattern is determined by the forward and backscattering properties of the mixed phase and rain and the backscattering properties of the ice. Therefore, DFRm could provide better performance in precipitation type classification and hydrometeor profile characterization than TRMM PR. In this research, two methods namely precipitation type classification method (PCM) and hydrometeor profile characterization (HPC) method are developed to perform profile classification for GPM-DPR using DFRm profile and its range variability. The methods have been implemented into GPM-DPR day one algorithm. Ground validation is an integral part of all satellite precipitation missions. Similar to TRMM, the GPM validation falls in the general class of validation and integration of information from space-borne observing platforms with a variety of ground-based measurements. Dual polarization ground radar is a powerful tool that can be used to address a number of important questions that arise in the validation process, especially those associated with precipitation microphysics and algorithm development. Extensive research has also been done regarding accurate retrievals of rain DSDs as well as attenuation correction for dual- polarization ground radar operating at S-, C- and X- band by using polarimetric measurements. However, polarimetric ground radar operating at a single frequency channel has limitation on DSD retrieval beyond rain region. A dual frequency and dual polarization Doppler radar (D3R) operating at the same frequency channels as GPM-DPR has been built. In this research, an algorithm is developed to retrieve DSD parameter for this D3R radar which will serve as GPM-DPR ground validation instrument.

Adviser: Dr. V. Chandrasekar
Co-Adviser: N/A
Non-ECE Member: Dr. Mielke, Statistics
Member 3: Dr. Jayasumana, ECE
Addional Members: Dr. Notaros, ECE

Publications:
Journal papers:

[1] M. Le and V. Chandrasekar, Raindrop Size Distribution Retrieval from Dual Frequency and Dual Polarization Radar, IEEE Transactions on Geoscience and Remote Sensing, Volume 50, No 5, May, 2012, pp 1748-1758.

[2] M. Le and V. Chandrasekar, Precipitation Type Classification Method for Dual Frequency Precipitation Radar (DPR) on board the GPM, IEEE Transactions on Geoscience and Remote Sensing, Volume 51, issue 3, 2012.

[3] M. Le and V. Chandrasekar, Hydrometeor profile characterization method for dual frequency precipitation radar (DPR) on board the GPM. IEEE Transactions on Geoscience and Remote Sensing, Volume 51, issue 6, 2012.

[4] A. Alqudoh, V. Chandrasekar and Minda Le, Investigating rainfall estimation from radar measurements using neural network. Accepted by Journal of Natural Hazards and Earth System Sciences (NHESS), 2012.

Conference papers:

[1] M. Le and V. Chandrasekar, Evaluation of GPM candidate algorithms on hurricane observations, AGU (American Geophysical Union) fall meeting, 2012, San Francisco, CA.

[2] M. Le and V. Chandrasekar, A potential DSD retrieval process for dual-frequency precipitation radar (DPR) on board GPM, SPIE Asia-pacific remote sensing 2012, Kyoto, Japan.

[3] V. Chandrasekar, Direk, Khajonrat and Minda, Le, Global vertical reflectivity profile analysis using TRMM PR observations: Application to tropical storms, The 4th Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) Mission International Science Conference, 2012, Tokyo, Japan.

[4] M. Le and V. Chandrasekar, Recent updates on precipitation classification and hydrometeor identification algorithm for GPM-DPR, Geoscience science and remote sensing symposium, IGARSS'2012, IEEE International, Munich, Germany.

[5] V. Chandrasekar, Mathew Schwaller, Manuel Vega, James Carswell, Kumar Vijay Mishra, Alex Steinberg, Cuong Nguyen, Minda Le, Joseph Hardin, Francesc Junyent, Jim George, Dual-frequency dual-polarized doppler radar (D3R) system for GPM ground validation: update and recent field observations, IGARSS'2012, IEEE International, Munich, Germany.

[6] V. Chandrasekar, Minda Le, Amin Alqudah and Delbert Willie, Global map of precipitation: An example of data fusion from satellite, ground radar and rain gauge. 92nd American Meteorological Society Annual Meeting , January 22-26, 2012.

[7] M. Le and V. Chandrasekar, Precipitation Type and Profile Classification for GPM-DPR, Geoscience science and remote sensing symposium, IGARSS'2011, IEEE International, Vancouver, Canada.

[8] M. Le and V. Chandrasekar, GPM Dual-frequency Ratio Characteristics in the Melting Layer, 35st Conference on Radar Meteorology, 26-30 September 2011, American Meteorology Society, Pittsburgh, PA.

[9] M. Le ,V. Chandrasekar and S. Lim, Microphysical retrieval from dual-frequency precipitation radar board GPM, Geoscience science and remote sensing symposium, IGARSS'2010, IEEE International, Honolulu, USA.

[10] M. Le ,V. Chandrasekar and S. Lim, Microphysical retrieval of dual-polarization and dual-frequency ground radar from GPM ground validation, Geoscience science and remote sensing symposium, IGARSS' 2010, IEEE International, Honolulu, USA.

[11] M. Le and V. Chandrasekar , Dual frequency and dual polarization radar observations of precipitation and retrievals for GPM ground validation. Proc USNC-URSI '2010, Boulder, Colorado.

[12] M. Le, V. Chandrasekar and S.Lim, Combined Ku and Ka band observations of precipitation and retrievals for GPM ground validation, Geoscience science and remote sensing symposium, IGARSS'2009, IEEE International, South Africa.

[13] M. Le, V. Chandrasekar and S.Lim , Microphysical retrieval from dual-frequency GPM observations, 34th Conf on Radar Meteorology. Amer. Meteor. Soc., Williamsburg, VA, 2009.

[14] V. Chandrasekar, Direk, Khajonrat, and Minda Le, Tropical Cyclone Nargis over Myanmar: Vertical structure and Microphysics based on Space-based Radar observations, Proc IEEE IGARSS'2008, Boston.

[15] Eugenio Gorgucci, Luca Baldini, V. Chandrasekar and Minda Le, Reflectivity and differential reflectivity rainfall algorithm performance at X-band, Proc IEEE IGARSS'2008, Boston.


Program of Study:
ECE795
ECE799
ECE512
EE742
EE549
EE672
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